2007 IEEE International Conference on Image Processing - San Antonio, Texas, U.S.A. - September 16-19, 2007

Technical Program

Paper Detail

Paper:MP-P5.8
Session:Biometrics III: Fingerprints, Iris, Palmprints
Time:Monday, September 17, 14:30 - 17:10
Presentation: Poster
Title: LEARNING APPEARANCE PRIMITIVES OF IRIS IMAGES FOR ETHNIC CLASSIFICATION
Authors: Xianchao Qiu; Institute of Automation, Chinese Academy of Sciences 
 Zhenan Sun; Institute of Automation, Chinese Academy of Sciences 
 Tieniu Tan; Institute of Automation, Chinese Academy of Sciences 
Abstract: Iris pattern is commonly regarded as a kind of phenotypic feature without relation to the genes. In our previous work, we argued that iris texture is race related, and its genetic information is illustrated in coarse scale texture features, rather than preserved in the minute local features of state-of-the-art iris recognition algorithms. In this paper, we propose a novel ethnic classification method based on learning appearance primitives of iris images. So we not only confirm that iris texture is race related, but also try to find out which kinds of iris visual primitives make iris images look different between Asian and non-Asian. In our scheme, we learned a small finite vocabulary of micro-structures, which are called Iris-Textons, to represent visual primitives of iris images. Then we use Iris-Texton histogram to capture the difference between iris textures. Finally iris images are grouped into two race categories, Asian and non-Asian, by Support Vector Machine(SVM). Based on the proposed method, we get a higher correct classification rate(CCR) of 91.02% than our previous method on a database containing 2400 iris samples.



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